Affiliation:
1. The University of Texas at Austin, Austin, TX, USA
2. IBM Research, Yorktown Heights, NY, USA
Abstract
Irregular programs are programs organized around pointer-based data structures such as trees and graphs. Recent investigations by the Galois project have shown that many irregular programs have a generalized form of data-parallelism calledamorphous data-parallelism. However, in many programs, amorphous data-parallelism cannot be uncovered using static techniques, and its exploitation requires runtime strategies such as optimistic parallel execution. This raises a natural question: how much amorphous data-parallelism actually exists in irregular programs?In this paper, we describe the design and implementation of a tool called ParaMeter that producesparallelism profilesfor irregular programs. Parallelism profiles are an abstract measure of the amount of amorphous data-parallelism at different points in the execution of an algorithm, independent of implementation-dependent details such as the number of cores, cache sizes, load-balancing, etc. ParaMeter can also generate constrained parallelism profiles for a fixed number of cores. We show parallelism profiles for seven irregular applications, and explain how these profiles provide insight into the behavior of these applications.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design,Software
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